Jump to main content
Jump to site search

Issue 2, 2017
Previous Article Next Article

Quantification of quality parameters in castanhola fruits by NIRS for the development of prediction models using PLS and variable selection algorithms on a laboratory scale

Author affiliations

Abstract

This paper proposes a novel methodology for the quantification of total phenolic compounds (TPCs) and total anthocyanin compounds (TACs) in castanhola fruits (Terminalia catappa Linn), using near infrared spectroscopy (NIRS) coupled with variable selection algorithms, such as interval partial least squares (iPLS) and genetic algorithm-partial least squares (GA-PLS). GA-PLS showed the best results in the prediction of both parameters. TPC parameters, Rp2 = 0.82, RMSEP = 11.3 mg GAE g−1 (mg gallic acid equivalents (GAE) per g sample), SEL 16.70 mg GAE g−1, RPD = 2.89, sensibility 2.19 × 10−7, and selectivity 0.048 were also obtained using first derivative (5 points) and MSC pretreatment. TAC parameters, Rp2 = 0.80, RMSEP = 8.70 mg L−1, SEL 6.93 mg L−1, RPD = 1.90, sensibility 6.73 × 10−6 and selectivity 0.07 were attained using second derivative (11 points) pre-treatment. From these findings, it can be concluded that NIRS coupled GA-PLS can be used as a non-destructive technique for determining TACs and TPCs in intact castanhola fruits.

Graphical abstract: Quantification of quality parameters in castanhola fruits by NIRS for the development of prediction models using PLS and variable selection algorithms on a laboratory scale

Back to tab navigation

Publication details

The article was received on 01 Sep 2016, accepted on 29 Nov 2016 and first published on 30 Nov 2016


Article type: Technical Note
DOI: 10.1039/C6AY02454H
Citation: Anal. Methods, 2017,9, 352-357
  •   Request permissions

    Quantification of quality parameters in castanhola fruits by NIRS for the development of prediction models using PLS and variable selection algorithms on a laboratory scale

    R. C. Costa, V. H. Uchida, T. B. Veríssimo Miguel, M. M. L. Duarte and K. M. G. Lima, Anal. Methods, 2017, 9, 352
    DOI: 10.1039/C6AY02454H

Search articles by author

Spotlight

Advertisements